While some organizations attempt to build in-house solutions, a platform approach tends to be more cost-effective and user- friendly. In-house development demands entire teams of developers and data scientists to build and maintain the system and its IT infrastructure. Often these solutions take years to build and are obsolete once they are completed due to the development time and lack of infrastructure flexibility. When choosing a platform, organizations may find that an open platform, which allows new sources to be integrated via an API and enables flexible modeling, is preferable, as it allows teams to benefit from a customized solution without the cost and hassle of building a bespoke solution. Now that we have explored the advantages of a platform approach, let’s deep dive into the kind of solutions available. 1 4 Decision intelligence platform 1 2 WHAT KIND OF DIGITAL INTELLIGENCE PLATFORMS ARE ON THE MARKET? There are several kinds of decision intelligence platforms and solutions on the market, each with its own benefits and drawbacks, suitable to different needs and organizations. Basic data fusion platforms enable the creation of a single data container. While some of these platforms may create unified entities and profiles, it is not a universal feature. This kind of solution attempts to free the analysts from the fusion problem, but still requires them to make manual queries and does not have the necessary analytics to generate automated insights on similarities and threat scoring. In addition, due to limited data modeling and analytics, these platforms are unable to integrate with sources that come in multiple formats and are generally restricted to structured databases. Since this solution is simple and low cost, it allows organizations on a budget to organize and sort their database and create simple identifiers, however, it is not an ideal solution for more complex data sources and analytical requirements. 3 On the market 3